Feature extraction of channel wave signal in coal seam based on phased source

Abstract

When the channel wave propagates in the coal seam and encounters an abnormal structure, the frequency, amplitude and other parameters will change. Receiving the channel wave signal clearly and extracting the time-frequency characteristics accurately are the keys to predict the abnormal structure ahead. In this paper, the phased source and new feature extraction method were employed for channel wave seismic exploration. The controllable phased source is used to generate channel wave. The CEEMDAN algorithm based on the EMD algorithm and the Fast ICA algorithm for blind source signal separation are combined new Fast ICA-CEEMDAN method for decomposing the channel wave signal. The homogeneous medium and the equivalent medium model of the mined-out coal measure stratum are established by the COMSOL multiphysics, the received channel wave signal is decomposed by Fast ICA-CEEMDAN method. The Hilbert marginal spectrum, time spectrum, instantaneous frequency spectrum and instantaneous frequency spectrum of channel wave signal were extracted. There are five characteristic parameters of phase spectrum and instantaneous amplitude spectrum. The results show that the method can accurately reflect the local characteristics of the channel wave signal, and has high time-frequency resolution, which provides favorable reference for coal mining.